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Related papers: Target Selection and Validation of DESI Quasars

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The Dark Energy Survey (DES) will be unprecedented in its ability to probe exceptionally large cosmic volumes to relatively faint optical limits. Primarily designed for the study of comparatively low redshift (z<2) galaxies with the aim of…

We present the VST ATLAS Quasar Survey, consisting of $\sim1,229,000$ quasar (QSO) candidates with $16<g<22.5$ over $\sim4700$ deg$^2$. The catalogue is based on VST ATLAS$+$NEOWISE imaging surveys and aims to reach a QSO sky density of…

We present the results of an optical spectroscopic survey of 46 heavily obscured quasar candidates. Objects are selected using their mid-infrared (mid-IR) colours and magnitudes from the Wide-Field Infrared Survey Explorer (WISE) and their…

Astrophysics of Galaxies · Physics 2017-12-27 R. E. Hviding , R. C. Hickox , K. N. Hainline , C. M. Carroll , M. A. DiPompeo , W. Yan , M. L. Jones

We present a catalog of 1,172,157 quasar candidates selected from the photometric imaging data of the Sloan Digital Sky Survey (SDSS). The objects are all point sources to a limiting magnitude of i=21.3 from 8417 sq. deg. of imaging from…

We present the technical details on how large-scale structure (LSS) catalogs are constructed from redshifts measured from spectra observed by the Dark Energy Spectroscopic Instrument (DESI). The LSS catalogs provide the information needed…

We conduct a pilot investigation to determine the optimal combination of color and variability information to identify quasars in current and future multi-epoch optical surveys. We use a Bayesian quasar selection algorithm (Richards et al.…

We present the steps taken to produce a reliable and complete input galaxy catalogue for the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey (BGS) using the photometric Legacy Survey DR8 DECam. We analyse some of the main…

The Dark Energy Spectroscopic Instrument (DESI) completed its five-month Survey Validation in May 2021. Spectra of stellar and extragalactic targets from Survey Validation constitute the first major data sample from the DESI survey. This…

Cosmology and Nongalactic Astrophysics · Physics 2024-10-18 DESI Collaboration , A. G. Adame , J. Aguilar , S. Ahlen , S. Alam , G. Aldering , D. M. Alexander , R. Alfarsy , C. Allende Prieto , M. Alvarez , O. Alves , A. Anand , F. Andrade-Oliveira , E. Armengaud , J. Asorey , S. Avila , A. Aviles , S. Bailey , A. Balaguera-Antolínez , O. Ballester , C. Baltay , A. Bault , J. Bautista , J. Behera , S. F. Beltran , S. BenZvi , L. Beraldo e Silva , J. R. Bermejo-Climent , A. Berti , R. Besuner , F. Beutler , D. Bianchi , C. Blake , R. Blum , A. S. Bolton , S. Brieden , A. Brodzeller , D. Brooks , Z. Brown , E. Buckley-Geer , E. Burtin , L. Cabayol-Garcia , Z. Cai , R. Canning , L. Cardiel-Sas , A. Carnero Rosell , F. J. Castander , J. L. Cervantes-Cota , S. Chabanier , E. Chaussidon , J. Chaves-Montero , S. Chen , X. Chen , C. Chuang , T. Claybaugh , S. Cole , A. P. Cooper , A. Cuceu , T. M. Davis , K. Dawson , R. de Belsunce , R. de la Cruz , A. de la Macorra , J. Della Costa , A. de Mattia , R. Demina , U. Demirbozan , J. DeRose , A. Dey , B. Dey , G. Dhungana , J. Ding , Z. Ding , P. Doel , R. Doshi , K. Douglass , A. Edge , S. Eftekharzadeh , D. J. Eisenstein , A. Elliott , S. Escoffier , P. Fagrelius , X. Fan , K. Fanning , V. A. Fawcett , S. Ferraro , J. Ereza , B. Flaugher , A. Font-Ribera , D. Forero-Sánchez , J. E. Forero-Romero , C. S. Frenk , B. T. Gänsicke , L. Á. García , J. García-Bellido , C. Garcia-Quintero , L. H. Garrison , H. Gil-Marín , J. Golden-Marx , S. Gontcho A Gontcho , A. X. Gonzalez-Morales , V. Gonzalez-Perez , C. Gordon , O. Graur , D. Green , D. Gruen , J. Guy , B. Hadzhiyska , C. Hahn , J. J. Han , M. M. S Hanif , H. K. Herrera-Alcantar , K. Honscheid , J. Hou , C. Howlett , D. Huterer , V. Iršič , M. Ishak , A. Jacques , A. Jana , L. Jiang , J. Jimenez , Y. P. Jing , S. Joudaki , E. Jullo , S. Juneau , N. Kizhuprakkat , N. G. Karaçaylı , T. Karim , R. Kehoe , S. Kent , A. Khederlarian , S. Kim , D. Kirkby , T. Kisner , F. Kitaura , J. Kneib , S. E. Koposov , A. Kovács , A. Kremin , A. Krolewski , B. L'Huillier , O. Lahav , A. Lambert , C. Lamman , T. -W. Lan , M. Landriau , D. Lang , J. U. Lange , J. Lasker , A. Leauthaud , L. Le Guillou , M. E. Levi , T. S. Li , E. Linder , A. Lyons , C. Magneville , M. Manera , C. J. Manser , D. Margala , P. Martini , P. McDonald , G. E. Medina , L. Medina-Varela , A. Meisner , J. Mena-Fernández , J. Meneses-Rizo , M. Mezcua , R. Miquel , P. Montero-Camacho , J. Moon , S. Moore , J. Moustakas , E. Mueller , J. Mundet , A. Muñoz-Gutiérrez , A. D. Myers , S. Nadathur , L. Napolitano , R. Neveux , J. A. Newman , J. Nie , R. Nikutta , G. Niz , P. Norberg , H. E. Noriega , E. Paillas , N. Palanque-Delabrouille , A. Palmese , P. Zhiwei , D. Parkinson , S. Penmetsa , W. J. Percival , A. Pérez-Fernández , I. Pérez-Ràfols , M. Pieri , C. Poppett , A. Porredon , S. Pothier , F. Prada , R. Pucha , A. Raichoor , C. Ramírez-Pérez , S. Ramirez-Solano , M. Rashkovetskyi , C. Ravoux , A. Rocher , C. Rockosi , A. J. Ross , G. Rossi , R. Ruggeri , V. Ruhlmann-Kleider , C. G. Sabiu , K. Said , A. Saintonge , L. Samushia , E. Sanchez , C. Saulder , E. Schaan , E. F. Schlafly , D. Schlegel , D. Scholte , M. Schubnell , H. Seo , A. Shafieloo , R. Sharples , W. Sheu , J. Silber , F. Sinigaglia , M. Siudek , Z. Slepian , A. Smith , M. T. Soumagnac , D. Sprayberry , L. Stephey , J. Suárez-Pérez , Z. Sun , T. Tan , G. Tarlé , R. Tojeiro , L. A. Ureña-López , R. Vaisakh , D. Valcin , F. Valdes , M. Valluri , M. Vargas-Magaña , A. Variu , L. Verde , M. Walther , B. Wang , M. S. Wang , B. A. Weaver , N. Weaverdyck , R. H. Wechsler , M. White , Y. Xie , J. Yang , C. Yèche , J. Yu , S. Yuan , H. Zhang , Z. Zhang , C. Zhao , Z. Zheng , R. Zhou , Z. Zhou , H. Zou , S. Zou , Y. Zu

We present a method of selecting quasars up to redshift $\approx$ 6 with random forests, a supervised machine learning method, applied to Pan-STARRS1 and WISE data. We find that, thanks to the increasing set of known quasars we can assemble…

We have conducted a pilot survey for z>3.5 quasars by combining the FIRST radio survey with the SDSS. While SDSS already targets FIRST sources for spectroscopy as quasar candidates, our survey includes fainter quasars and greatly improves…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-14 Ian D. McGreer , David J. Helfand , Richard L. White

The DESI survey will observe more than 8 million candidate luminous red galaxies (LRGs) in the redshift range $0.3<z<1.0$. Here we present a preliminary version of the DESI LRG target selection developed using Legacy Surveys Data Release 8…

A number of deep, wide-field, near-infrared surveys employing new infrared cameras on 4m-class telescopes are about to commence. These surveys have the potential to determine the fraction of luminous dust-obscured quasars that may have…

Astrophysics · Physics 2009-11-11 Natasha Maddox , Paul C. Hewett

Accurate redshift estimates are a critical requirement for weak lensing surveys and one of the main uncertainties in constraints on dark energy and large-scale cosmic structure. In this paper, we study the potential to calibrate photometric…

We present the one-dimensional Lyman-$\alpha$ forest power spectrum measurement using the first data provided by the Dark Energy Spectroscopic Instrument (DESI). The data sample comprises $26,330$ quasar spectra, at redshift $z > 2.1$,…

The Early Data Release (EDR) of the Dark Energy Spectroscopic Instrument (DESI) comprises spectroscopy obtained from 2020 December 14 to 2021 June 10. White dwarfs were targeted by DESI both as calibration sources and as science targets and…

We present a new algorithm to estimate quasar photometric redshifts (photo-$z$s), by considering the asymmetries in the relative flux distributions of quasars. The relative flux models are built with multivariate Skew-t distributions in the…